Refer to the data on fixing breakdowns in cell phone relay towers in the table on TAB 2. In the initial design, experience level was coded as Novice or Guru. Now consider three levels of experience: Novice, Guru and Experienced. Some additional runs for an experienced engineer are given below. Also, in the original data set, reclassify Guru in run 3 as Experienced and Novice in run 14 as Experienced.Keep all the other numbers for these two engineers the same.With these changes and the new data below, perform a multivariate multiple regression analysis with assessment and implementation times as the responses, and problem severity, problem complexity and experience level as the predictor variables. Consider regression models with the predictor variables and two factor interaction terms as inputs. (Note:The two changes in the original data set and the additional data below unbalances the design, so the analysis is best handled with regression methods.)
1. Conduct a regression analysis and a multivariate multiple regression analysis using the data in the table.
2. Describe the results of the analysis.
3. Create a results table.
4. Provide your interpretation of the results
5. Discuss the assumptions underlying the analyses
6. Compare and contrast multiple discriminant analysis, regression analysis, logistic regression, and analysis of variance (ANOVA).
7. Include citations of scholarly research that support your conclusions.
I have answered the questions in the Excel Sheet (separate Tabs for each).
Results and Interpretation:
All the predictor variables are significant at 5% level (p value < .05)
The model explains 94.5% variation in Assessment time (R squared value)
When Severity changes from 'Low' to 'High', assessment time increases by 2.15 minutes on an average
When Complexity changes ...
The solution provides a detailed discussion of the regression analysis, and multivariate regreesion analysis. Here the tables have been created and the complete interpreatations are also presented.